One approach to improve the performance of the algorithm would be to prioritize certain letters based on their position in the word. For example, if the letter "e" appears most frequently in the possible words but is already in the correct position in the masked word, it would make more sense to guess a letter that appears less frequently but is not in the correct position.
Additionally, taking into account the number of incorrect guesses made so far and adjusting the strategy accordingly could also improve performance. For example, if there are only a few incorrect guesses remaining, it might make more sense to guess more conservatively and prioritize letters that are likely to appear in more common words.
It would also be useful to keep track of the letters that have been guessed correctly and use that information to eliminate possible words from the dictionary, further reducing the pool of possible words and improving the accuracy of letter frequency calculations.
Finally, incorporating word length into the algorithm could also be beneficial. For example, if the masked word is very short, it might make sense to prioritize letters that appear more frequently in short words.
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